Seismic surface waves are often measured in exploration seismic survey in land or shallow-water environment. These surface waves typically exhibit dispersion, a physical phenomenon where different frequency components of the waves propagate at different speeds. Estimation of velocity dispersion is essential to noise mitigation and shallow earth characterization. In shallow earth seismic propagation, dispersion results from the fact that different frequencies probe to different depths in the near surface of the earth, and in a characteristically layered earth the velocities of deeper sediments are higher than the velocities of the sediments right near the earth's surface. By characterizing dispersion, the surface waves that travel along the earth's near surface can be characterized. Since such surface waves almost always represent undesirable noise in seismic data, surface-wave characterization permits the accurate removal of such noises. Surface-wave characterization also permits the determination of local earth properties in the vicinity of a seismic survey (Lee and Ross, 2009, WO 2009/120401 A1 and WO 2009/120402 A1; Park, et al. 2007).
The general methods of surface-wave characterization include:                Multi-channel analysis of surface waves (“MASW”) for local, site-specific analysis—permits detailed analysis and signal processing on data (Park, et al. 2007).        For larger quantities of data, covering larger areas, or involving massive 3-D seismic surveys, there is a need for some automation and integration of estimation, quality control, visualization and mapping. Global seismology is an intermediate case between local, site-specific data analysis and massive 3-D seismic surveys, but data sets are still small enough to be mostly hand interpreted with the aid of analysis software (Herrmann, R. B., 2002) and visualization. The end member in terms of methods to deal with massive 3-D seismic surveys is represented by Lee and Ross (2009, WO 2009/120402 A1), where the surface wave velocity V is estimated as a function of two spatial coordinates x and y, and frequency f.        Other methods are more complete in the formalization of the inversion, such as that of Krohn (2010), Strobbia and Glushchenko (2010) and Baumstein, et al., (2011) using various forms of approximate or full-wave inversion to derive either dispersion properties (Krohn, Strobbia and Glushchenko) or earth properties (Baumstein, et al.).        